Texture and Color Features based Color Image Retrieval using Canonical Correlation

Texture and Color Features based Color Image Retrieval using Canonical Correlation

K. Seetharaman

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Bachala Shyam Kumar

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Puducherry Technological University

Texture and Color Features based Color Image Retrieval using Canonical Correlation

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Abstract

This paper proposes a novel technique, based on Canonical correlation analysis, and the Chi-square test is employed to test the significance of the correlation coefficients. If it is significant, then it is concluded that the input query and target images are same or similar; otherwise, it is inferred that the two images are significantly different. In order to experiment the proposed canonical correlation method, a database is designed and constructed with the help of different types of images and their feature vectors. The F β -measure is applied to evaluate the performance of the proposed method. The obtained results expose that the proposed technique yields better results than the existing.

References

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

K. Seetharaman. 2016. \u201cTexture and Color Features based Color Image Retrieval using Canonical Correlation\u201d. Global Journal of Research in Engineering - J: General Engineering GJRE-J Volume 15 (GJRE Volume 15 Issue J6).

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GJRE Volume 15 Issue J6

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Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

Keywords

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Classification

GJRE-J Classification FOR Code: 080106

Submission ReceivedFebruary 11, 2015
Peer Review Double Blind
Handling Editor
Accepted March 1, 2015
Published March 15, 2015

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v1.2

Issue date

January 17, 2016

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Article Matrices

Total Score: 102

Country: India

Subject: Global Journal of Research in Engineering - J: General Engineering

Authors: K. Seetharaman, Bachala Shyam Kumar (PhD/Dr. count: 0)

View Count (all-time): 190

Total Views (Real + Logic): 3980

Total Downloads (simulated): 2051

Publish Date: 2016 01, Sun

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Total Views: 3980

Total Downloads: 2051

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